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This paper examines the potential of solar and hydrogen (H 2) energy-based hybrid energy systems for residential applications. The growing need for energy and the demand for sustainable energy sources have led to the development of integrated energy systems that combine renewable energy resources to meet energy needs. This paper overviews recent studies on hybrid energy systems for on-grid and off-grid residential utilizations. It discusses the system configuration and components of hybrid energy systems, including solar panels, electrolyzers, fuel cells (FC), and batteries. It also covers the technical optimization of integrated energy systems, including sizing, control strategies, and economic analysis. The key findings of this review paper indicate that hybrid energy systems can offer dependable and sustainable energy for residential applications. Through numerical analyses, the optimal dimensioning of the system elements and control strategies can significantly enhance the system's performance and lower the cost of energy. This study also highlights the challenges and opportunities for integrating hybrid energy systems within residential applications. Overall, it provides in-depth perspectives on the possibilities inherent in solar and hydrogen energy-based hybrid energy systems for residential applications. The findings can guide future research and the advancement of hybrid energy systems for sustainable energy solutions. • Comprehensive review on solar and hydrogen-based residential applications. • Holistic approach to system configuration, optimization, and economics. • Detailed analysis of interconnected components enhancing system efficiency. • Unique focus on real-world residential applications and scenarios. • Broad applicability across diverse geographical regions. [ABSTRACT FROM AUTHOR]

Deploying renewable energy to unit design energy-efficient technologies may fulfill the additional demand of various energy-intensive industries for their sustainability and resiliency. Multiple Stage Evaporator (MSE) is one of the most energy-intensive units used to extract the water content of the weak liquor in various industries, including the paper industry. This energy intensiveness may be reduced by integrating various Energy Reduction Schemes (ERSs). Hence, this work proposes a ERSs integrated MSE model to analyze its energy efficiency. These ERSs includes Thermo-Vapor Compressor, Steam-, Feed- Split, Feed Preheater, and Flash Tanks. Further, the performance of the proposed model is investigated under two important real-time plant complexities: Boiling Point Elevation and Fouling to achieve more realistic results. The performance analysis is initiated with the formulation of a nonlinear constrained optimization problem to increase the steam economy (SE). Also, the simulation is extended to validate at two different product concentrations (52% and 65%) by employing state-of-art optimization algorithms: CONOPT, and SCA in GAMS and MATLAB respectively. The simulated results shows an increment 1.64% and 1.37% of SE for both 52% and 65% concentration of weak liquor respectively in case of CONOPT than SCA. Also, the waste heat of the condensate, feed, and product may be further utilized for the heat recovery by incorporating the flash tanks which leads to a countable energy saving. Eventually, integrating the solar fields: PTC and LFR ensures a notable reduction in conventional heat utilization by 85.96% and 92.85%, respectively and hence, enhance the energy efficiency. • Expounded energy modeling of ERSs based MSE with BPE and Fouling. • Implementation of NLP and metaheuristic approaches for performance optimization. • Reutilization of waste heat to maximize the energy efficiency. • Integration of solar fields (PTC and LFR) to reduce conventional fuel utilization. • Prospecting the challenges and direction of energy management optimization. [ABSTRACT FROM AUTHOR]

Due to the widespread use of multi-generation systems utilizing renewable energy sources and the growing global demand for such systems from both economic and environmental considerations, numerous researchers have focused on the design and evaluation of their performance. To this end, this research presents a biomass-based multi-generation system with an innovative and practical design that can generate electricity, heat, and hydrogen. This system includes a modified gas turbine cycle, a supercritical CO 2 (SCO 2) cycle, a transcritical CO 2 (TCO 2) cycle, a proton exchange membrane (PEM) electrolyzer, and a PEM fuel cell unit. This study aims to evaluate the impact of various biomass sources (paper, wood, paddy husk, and municipal solid waste) on the system performance. The proposed system has been analyzed using the first and second laws of thermodynamics. This system uses the maximum capacity to produce power, heat and hydrogen. A fuel cell unit has been used to consume hydrogen and generate more electricity. In the basic mode, the system has energy and exergy efficiencies of 47.89% and 32.26%, respectively, and can produce 2.74 kg/h of hydrogen. The biomass fuel consumption rate within the system is 0.055 kg/s. The overall exergy destruction of the system amounts to 1240 kW, with the biomass boiler and the condenser being the components that experience the greatest exergy destruction, registering values of 535.5 kW and 432.3 kW, respectively. Notably, employing municipal waste as biomass increases the system's exergy efficiency to 33.16%. • To investigate a biomass-driven system for producing power, hydrogen, and heating. • To evaluate the impact of various biomass sources on the system performance. • To use PEME for hydrogen and PEMFC for power and heat production. [ABSTRACT FROM AUTHOR]

There is a great desire to integrate multiple energy systems by forming low-carbon energy hubs. Among various energy platforms, the integration of power and gas networks via Power-to-Gas (PtG) technologies is introduced as a promising solution to enhance the flexibility of power grids and facilitate seamless adoption for high penetration levels of renewable energy resources. In addition, the production of green hydrogen from waste/inexpensive clean electricity has recently been identified as a potential means for large-scale energy storage, deployment of hydrogen mobility, and decarbonization of several processes that utilize hydrogen. As integrated hydrogen-based energy hubs (H 2 Hubs) attract more attention for widespread deployment, the security of such new platforms against various cyberattacks is also becoming a critical topic for investigation. This paper proposes a new data estimation technique, developed and integrated with H 2 Hubs scheduling models, for real-time optimal adaptive collection and organization of the system operating parameters for cybersecurity assessment. A new formulation is presented for the adaptive formation of a newly proposed concept, referred to as the system feasibility area , via real-time acquisition of the system operating information. The created feasibility areas are utilized for real-time post-occurrence detection of the bad scheduling data that is invisible to the existing cybersecurity layers. Numerical studies are conducted to demonstrate the efficacy and feasibility of the proposed model. The results demonstrate that the historical data can be adaptively collected in real time and successfully utilized to create feasibility areas to categorize the system operating points. • An optimal scheduling model is proposed for hydrogen-based energy hubs (H 2 Hubs). • A new data estimation method is developed and integrated with the scheduling model. • A new formulation is given for the adaptive creation of the feasibility area. • Simulation case studies are presented and discussed. [ABSTRACT FROM AUTHOR]

The shared energy storage system is recognized as a promising business model for the coordinated operation of integrated energy systems (IES) to improve the utilization of energy storage and the consumption of renewable energy. As the hydrogen energy gradually receives more attention, this paper constructs the structure of a hybrid hydrogen energy storage system shared by an IES alliance in a dynamic pricing mode. A bi-level optimization model for the shared hybrid hydrogen energy storage system (SHHESS) is proposed to optimize the capacity configuration decisions and the pricing strategy jointly. The upper level determines the capacity and dynamic price of SHHESS with maximum profits and the lower level obtains the optimal operation of the IES alliance minimizing the total operation costs. The proposed model is solved by an improved PSO-GA algorithm and CPLEX solver. Finally, numerical tests are conducted in different scenarios. The results show that the hybrid energy storage system improves the daily profits of SHHESS by 70.3% and 5.44%, and reduces the renewable energy curtailment by 80.93% and 48.92% respectively compared to the battery-only and hydrogen-only systems. Additionally, the daily operation cost of the IES alliance is 35.2% lower than the individual operation scenario. The proposed model confirms the feasibility and superiority of the hybrid hydrogen energy storage system in a sharing business mode. • Design an interactive structure of a shared hybrid hydrogen energy storage system. • Propose a bi-level planning optimization framework for shared hybrid hydrogen energy storage. • The dynamic price of energy storage sharing service is optimized. • Determine the optimal operation strategy of the integrated energy system alliance. • Propose a hybrid method combining an improved PSO-GA and CPLEX optimizer. [ABSTRACT FROM AUTHOR]

The measures needed to limit global warming pose a particular challenge to current fossil fuel exporters, who must not only decarbonise their local energy systems, but also compensate for the expected decline in fossil fuel revenues. One possibility is seen in the export of green hydrogen. Using Algeria as a case study, this paper analyses how different levels of ambition in hydrogen exports, energy efficiency and fuel switching affect the cost-optimal expansion of the power sector for a given overall emissions reduction path. Despite falling costs for photovoltaics and wind turbines, the results indicate that in countries with very low natural gas prices, such as Algeria, a fully renewable electricity system by 2050 is unlikely without appropriate policy measures. The expansion of renewable energy should therefore start early, given the high annual growth rates required, which will be reinforced by additional green hydrogen exports. In parallel, energy efficiency is a key factor as it directly mitigates CO2 emissions from fossil fuels and reduces domestic electricity demand, which could instead be used for hydrogen production. Integrating electrolysers into the power system could potentially help to reduce specific costs through load shifting. Overall, it seems advisable to analyse hydrogen exports together with local decarbonisation in order to better understand their interactions and to reduce emissions as efficiently as possible. These results and the methodology could be transferred to other countries that want to become green hydrogen exporters in the future and are therefore a useful addition for researchers and policy makers. • The required strong capacity expansion for PV and wind is challenging, but feasible. • "Energy efficiency first" benefits both the local energy transition and H2 exports. • Fully renewable power systems require a suitable political framework. • Higher hydrogen exports might help to reduce the specific power system cost. • Fossil capacity expansion must be stopped to avoid lock-ins and higher future costs. [ABSTRACT FROM AUTHOR]

The development of large energy systems based on renewable energy sources is accompanied by an increase in the input capacities of large grid storages. Taking into account the vector for decarbonization and maneuverability, the use of hydrogen as a fuel in the cycle of a diabatic compressed air energy storage (CAES) is a promising scientific and technical direction. This paper analyzes the key performance indicators of a compressed air energy storage in the presence and absence of thermal energy recovery within the cycle. In addition, an assessment was made of the prospects for the use of a methane-hydrogen mixture in gas turbines. At the end of the paper, a calculation of the process of plasma pyrolysis of methane is given as one of the possible methods for the production of hydrogen for use in energy purposes. [ABSTRACT FROM AUTHOR]

In the context of renewable energy systems, microgrids (MG) are a solution to enhance the reliability of power systems. In the last few years, there has been a growing use of energy storage systems (ESSs), such as hydrogen and battery storage systems, because of their environmentally-friendly nature as power converter devices. However, their short lifespan represents a major challenge to their commercialization on a large scale. To address this issue, the control strategy proposed in this paper includes cost functions that consider the degradation of both hydrogen devices and batteries. Moreover, the proposed controller uses scenarios to reflect the stochastic nature of renewable energy resources (RESs) and load demand. The objective of this paper is to integrate a stochastic model predictive control (SMPC) strategy for an economical/environmental MG coupled with hydrogen and battery ESSs, which interacts with the main grid and external consumers. The system's participation in the electricity market is also managed. Numerical analyses are conducted using RESs profiles, and spot prices of solar panels and wind farms in Abu Dhabi, UAE, to demonstrate the effectiveness of the proposed controller in the presence of uncertainties. Based on the results, the developed control has been proven to effectively manage the integrated system by meeting overall constraints and energy demands, while also reducing the operational cost of hydrogen devices and extending battery lifetime. • Implementation of an SMPC strategy based on a scenario-based approach. • Reduction of operation and maintenance costs and integration of uncertainties. • Minimization of the overall operational costs and maximization the profits. • Reduction of complexity and computational time. • Implementation of a unique control architecture to manage a microgrid in different modes. [ABSTRACT FROM AUTHOR]

Under the dual pressure of energy consumption and environmental pollution, mankind hopes to develop clean and renewable alternative energy, and the rapid development of fuel cells meets people's demand for energy-efficient power systems. The emergence of portable micro energy systems represented by microfluidic fuel cells, such as paper-based microfluidic fuel cells, has greatly enriched the means of medical detection to better cope with the threat of disease transmission. In this work, the numerical simulation method is innovatively introduced to study the paper-based microfluidic fuel cells. Both transient and steady-state modes are employed to demonstrate the whole operation process of the paper-based microfluidic fuel cell. In addition, the different structural parameters, including electrode spacing, the distance between electrode and inlet, channel thickness, and electrode length, are also investigated their influence mechanisms on cell performance. Results show that the increase of most structural parameters decreases cell output power in different degrees. Even on the premise that increasing channel thickness has a positive impact on the output power, the fuel utilization still shows a downward trend. These conclusions provide theoretical support and reference for future optimization work and accelerate the development of microfluidic fuel cells. • Numerical simulation is employed to study paper-based microfluidic fuel cell. • The effects of structure parameters on cell performance are discussed. • Through fuel concentration distribution to reveal cell performance mechanism. • Fuel utilization is used to evaluate energy efficiency. [ABSTRACT FROM AUTHOR]

• A life cycle assessment (LCA) of solid recovered fuel (SRF) was conducted. • SRF production process contributes to about 35.6 kg CO 2 -eq per ton. • A maximum of −1752.03 kg CO 2 -eq was obtained with about 80 % of SRF biogenic carbon. • A footprint of −542.09 to −1729.05 kg CO 2 -eq can be found due to coke substitution. • The study recommended SRF production to mitigate the global carbon footprint. Solid recovered fuel (SRF) from non-recyclable waste obtained from source separation and mechanical treatments can replace carbon coke in cement plants, contributing to the carbon neutrality. A life cycle assessment (LCA) of the SRF production from non-recyclable and selected waste was conducted in an Italian mechanical treatment plant to estimate the potential environmental impacts per ton of SRF produced. The analysis would contribute to evaluate the benefits that can be obtained due to coke substitution in best- and worst-case scenarios. The avoided impacts achieved were assessed, together with an evaluation of the variables that can affect the environmental benefits: SRF biogenic carbon content (in percentage of paper and cardboard); transportation distances travelled from the treatment plant to the cement kiln; the renewable energy used in the mechanical facility. On average, about 35.6 kgCO 2 -eq are generated by the SRF transportation and production phase. These impacts are greatly compensated by coke substitution, obtaining a net value of about −1.1 tCO 2 -eq avoided per ton of SRF. On balance, the global warming potential due to SRF production and consumption ranges from about −542 kgCO 2 -eq to about −1729 kgCO 2 -eq. The research recommended the use of SRF to substitute coke in cement kilns also in low densely-populated areas to mitigate environmental impacts and achieve carbon neutrality at a global level. [ABSTRACT FROM AUTHOR]

This paper examines the complex relationship between the role of H 2 , carbon emissions and their impact on global warming and the economy. Despite improvements in energy efficiency, fossil fuel consumption continues to increase. CO 2 from industrial activities at high temperatures, such as cement, iron, steel and glass production, have increased rapidly, resulting in an increase in the concentration of greenhouse gases in the atmosphere. These emissions accelerate climate change, leading to dangerous consequences such as increasing average atmospheric temperature and decreasing agricultural productivity. To combat this, it is advocated to reduce CO 2 emissions by using renewable energy sources such as hydroelectricity, biomass, wind solar energy. Current study also discusses carbon reduction methods, including oxy-fuel combustion capture, pre-combustion capture, and post-combustion capture. Despite their unique advantages and disadvantages, these methods play an important role in reducing CO 2 emissions from power plants. Additionally, the article highlights the importance of H 2 as a cornerstone in the development of synthetic fuels and future energy systems. H 2 from renewable sources holds the potential to use carbon-neutral synthetic liquid fuels and revolutionize transportation. Although traditional H 2 production methods are associated with emissions, sustainable H 2 production techniques can facilitate low-carbon fuel production. The article concludes by highlighting the importance of sustainable energy practices and the role of H 2 in reducing carbon emissions, highlighting research efforts to improve production methods, integrate renewable energy, and develop carbon capture technologies for a sustainable future. • Methods used in synthetic fuel production and sources of hydrogen production. • Carbon capture methods and their comparative discussion. • The importance of hydrogen production in synthetic fuel production and future plan. [ABSTRACT FROM AUTHOR]

This paper investigates the impacts of economic (in)stability on carbon emissions and the role of renewable energy in these effects at the crossroads of accelerated climate change and rising global economic instability. The paper hypothesizes that these implications should be examined not by direct impacts across variables, but rather via indirect effects serially mediated by renewable energy consumption and economic growth. This paper analyzes the United States from January 1980 and April 2022 using manifest structural equation modeling. The paper reaches two major conclusions. First, there are clear distinctions between (i) the direct and indirect effects of economic stability, surrogated by inflation and policy interest rate, on carbon emissions, (ii) the symmetric and asymmetric indirect effects, and (iii) the roles of aggregate renewable energy and its components, such as biomass and hydropower energy use, in mediating these symmetric and asymmetric indirect effects. Second, renewable energy significantly reduces the carbon-increasing effects of inflation and interest rates. The paper contains proper policy suggestions based on the findings. [ABSTRACT FROM AUTHOR]

With further penetration of low-carbon energy conversion, microgrids (MGs) have become a necessary tool for expanding the consumption of renewable energies. In this paper, an optimal operation model for a microgrid-based multi-agent system is proposed. The goal is to save the total energy cost, which is expressed as a sum of locally observable convex functions. Therefore, improving the operational efficiency of microgrids is the key to promoting renewable energy development. This paper develops a three-layer multi-agent system model considering energy storage system and power thermal load demand response to solve the energy management problem of microgrids. In order to investigate the effect of energy storage system and demand response in microgrids, this paper designs three simulation cases, namely infrastructure case, energy storage case and demand response case. In order to prove the effectiveness of the proposed method, this paper uses the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) the multi-agent system model can realize the joint optimization of "resource, network, load and storage". (2) The introduction of energy storage and demand response system in microgrids can stabilize the output. Renewable energy units promote the use of renewable energy and reduce the overall operating cost of microgrids. Moreover, the results clearly demonstrate that the proposed algorithm has far better performance than other optimization methods. Also, the analysis obtained from the results shows that the cost is reduced by 1.82%. PV and WT output increased by 14.54% and 2.42%. In addition, their standard deviation decreases after ESS participation. The proposed approach is very effective through a simulation case study, which shows high potential for applications. [ABSTRACT FROM AUTHOR]

Regional integrated energy systems (RIES) can economically and efficiently use regional renewable energy resources, of which energy storage is an important means to solve the uncertainty of renewable energy output, but traditional electrochemical energy storage is only single electrical energy storage, and the energy efficiency level is low. Hydrogen energy storage has the advantages of large energy storage capacity, long storage time, clean and pollution-free, and can realize the synergistic and efficient utilization of electricity and thermal power. Based on this, this paper proposes a synergistic planning method for an integrated energy system with hydrogen storage taking into account the coupled use of electric-thermal energy, which effectively reduces the system carbon emission and improves the comprehensive energy efficiency level. Firstly, this paper constructs an electric-thermal coupling model of the hydrogen energy storage unit and proposes an optimization strategy for the integrated energy system containing hydrogen storage taking into account the utilization of electricity and thermal power. Secondly, a planning optimization model with the lowest economy and carbon emission and the highest comprehensive energy efficiency was constructed. Third, the CSPO-GE optimization algorithm is proposed for solving the problem, which significantly improves the solution efficiency. Finally, a planning optimization simulation of RIES for a residential community W in northern China verifies the effectiveness of the model and method proposed in this paper. The comparative analysis of the three schemes shows that compared with the integrated energy system with conventional electrochemical energy storage and heat storage tank as the main form of energy storage and the integrated energy system with only hydrogen storage, the integrated energy system with hydrogen storage and heat storage tank can reduce carbon emissions by 43.8% and 7.61%, respectively, and improve the integrated energy efficiency level by 337.14% and 14.44%. • An electrothermal coupled production strategy based on dynamic equilibrium feedback regulation is proposed. • A hydrogen-containing RIES planning and optimization model considering economy-environment-efficiency is constructed. • A multi-objective chaotic particle swarm algorithm (CPSO-GE) based on greedy and elite retention strategies is proposed • The impact of cost variation of hydrogen storage devices on the economics of integrated energy systems is considered. [ABSTRACT FROM AUTHOR]

The present paper analyses the evolution of renewable energy generation in the European Union through a decomposition analysis based on the Index Decomposition Analysis together with the Logarithmic Mean Divisia Index within the EU27 between 2000 and 2020. A four factors decomposition approach is considered for decomposing the total RES generation and a five factors model is employed to decompose the carbon emissions. Furthermore, a focus on wind and solar photovoltaic generation is introduced through a four factors decomposition calculated in the period 2010–2020. The most influential factors affecting the RES generation trend in the period 2000–2020 are the RES share and energy efficiency wich determined an increase of 1841 TWh and a decrease of 635 TWh respectively. Variations of carbon emissions are mostly affected by the energy intensity, namely the amount of energy necessary to produce one unit of GDP, which determined a reduction of 1040 Mt. Through the decomposition analysis, the paper successfully identifies the specific drivers supporting RES development and controlling carbon emissions, thus adequate policy measures can be designed to reach planned targets. • LMDI methodology is used to study decomposition of RES generation in EU. • Technical and socio-economic factors are highlighted by using 4 or 5 factors identity. • Technical factors have the main impact on the increase in RES generation. [ABSTRACT FROM AUTHOR]

The transition to a low-carbon energy system can be depicted as a "great reconfiguration" from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district. • Hydrogen role in the transition to low carbon energy systems for urban energy district. • Data-driven urban energy modelling using regression-based approaches. • Probabilistic modelling of energy demand in terms of electricity and fuels. • Climate change impact and energy efficiency measures accounting. • Seasonal variations of energy demand patterns from short-term to long-term scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system. • An efficient energy storage system is essential for managing intermittent energy supply. • The fuel cell can generate DC power by combining hydrogen with oxygen. • The amount of power generated by a PV panel depends on temperature and solar radiation intensity. • Deterministic rule-based controllers operate based on pre-defined rules. • Energy Management System coordinate the flow of power between different components. [ABSTRACT FROM AUTHOR]

Optimal energy management of microgrids enables efficient integration of renewable energies by considering all system flexibilities. For systems with significant seasonal imbalance between energy production and demand, it may be necessary to integrate seasonal storage in order to achieve fully decarbonized operation. This paper develops a novel model predictive control strategy for a renewable microgrid with seasonal hydrogen storage. The strategy relies on data-based prediction of the energy production and consumption of an industrial power plant and finds optimized energy flows using a digital twin optimizer. To enable seasonal operation, incentives for long-term energy shifts are provided by assigning a cost value to the storage charge and adding it to the optimization target function. A hybrid control scheme based on rule-based heuristics compensates for imperfect predictions. With only 6% oversizing compared to the optimal system layout, the strategy manages to deliver enough energy to meet all demand while achieving balanced hydrogen production and consumption throughout the year. • PV with seasonal H 2 storage enables fully sustainable operation of industrial microgrids. • Model predictive control overcomes perfect foresight limitation in energy management. • H 2 production for long-term storage is incentivized by adding an extra cost term. • Hybrid predictive control enables a low cost system with nearly perfect yearly operation. [Display omitted] [ABSTRACT FROM AUTHOR]

• A simple, large-scale fabrication of cooling paper via pulping and papermaking technology. • The cooling paper is facilely deconstructed and regenerated to architect the secondary cooler. • The cooling paper features a high solar reflectance of 94% and emissivity of 0.95. • The cooling paper shows the sub-ambient temperature drop of 6 ∼ 8.8 °C under directly solar radiation at daytime. Passive radiative cooling materials provide coldness without energy consumption for all-day thermal comfort by reflecting solar irradiation and emitting heat into the 3 K universe. However, the conventional radiative cooling materials involve complex multilayer structures and unsustainable polymers, showing the non-recyclable disadvantage, which induces resource waste and environmental issues. Herein, we reported a low-cost, scalable, and eco-friendly radiative cooling material (namely cooling paper), consisting of the delignified, fibrillated cellulose fibers and nano-sized hydroxyapatite (HA) via the mature pulping and papermaking process. The resulting cooled paper can be recycled, and it can be easily deconstructed to harvest cellulose fibers and HA, individually. The recovered source materials can be reused to prepare secondary products that show comparable performance to the original cooling paper, including a high solar reflectance of ∼94% and an infrared emissivity of ∼0.95 in the atmospheric transparency window. Such cooling paper enables superior cooling performance with the temperature drop of 6 ∼ 8.8 °C under directly solar radiation. Based on the EnergyPlus simulation, our cooling paper shows a average cooling energy saving of ∼29 % in buildings across China. The recyclable cooling paper with high cooling capability and scalability, as well as environmental friendliness, shows promising potential for sustainable energy-efficient buildings. [ABSTRACT FROM AUTHOR]

This paper probes the effectiveness of competitive industrial performance (CIP) and renewable energy in enhancing load capacity factor in top-10 CIP economies for the period 1990–2018. We run panel econometric techniques that address cross-sectional dependence, endogeneity and heterogeneity to provide policy recommendations with the applications of industry, innovation, and infrastructure (SDG 9), which is linked to affordable and clean energy (SDG 7) and climate action (SDG 13). In the empirical analysis, two different environmental quality indicators such as CO 2 emissions and load capacity factor are used. While cointegration between variables cannot be detected in the emissions model, evidence for the existence of cointegration is presented in the load capacity factor model. The findings in the paper suggest that economic growth and competitive industrial performance adversely impact environmental quality, while renewable energy consumption and human capital can improve load capacity factor. The result shows that human capital and renewable energy consumption can be strong tools for stimulating load capacity factor in top-10 CIP economies. Countries with high competitive industrial performance need to return to a green economy without losing their competitiveness. • SDG-based environmental policies was presented for the top-10 CIP economies. • A battery of second generations methods was employed. • Investigating the impacts of Competitive industrial performance on environmental quality. • Competitive industrial performance has a negative impact on environmental quality. [ABSTRACT FROM AUTHOR]

This paper collects monthly data for the United States from January 2005 to April 2021 and develops a time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model to investigate the time-varying relationship between climate policy uncertainty, oil prices, and renewable energy consumption. In addition, this paper discusses the dynamic impact of climate policy uncertainty on five types of renewable energy consumption. Our results show that the relationship between them is time-varying. In most periods, climate policy uncertainty positively affects oil prices in the short and medium term, and positively affects total renewable energy consumption in the short and long term. In addition, the impact of climate policy uncertainty on the consumption of the five types of renewable energy is heterogeneous. The results of the robustness tests indicate that our results are robust and our study has important implications for the development of relevant policies. [ABSTRACT FROM AUTHOR]

World's energy demand is majorly met by fossil fuels. An increase in the demand for energy and the depletion of fossil fuels leads to look for the alternate source of energy. Hydrogen is one of the most viable alternate sources of alternate energy. This paper presents the performance study of a Compression Ignition engine using a fuel combination of diesel and hydrogen-diesel. The performance parameters have been analyzed with two input factors, load and Compression Ratio and three output responses, Brake Thermal efficiency (BTE), Brake Specific Fuel Consumption (BSFC) and Volumetric efficiency. The experimental results indicate the improvement in BTE, reduction in BSFC and volumetric efficiency. The BTE was improved by 6.38%, BSFC was reduced by 4.87% and Volumetric efficiency got reduced by 1.89% when hydrogen-diesel fuel is used in place of neat diesel. The experiments have been designed with the help of Design Expert® 13.0.5 using Response Surface Method. The experiments are conducted using Optimal (Custom) design. Mathematical relations are developed between the process parameters and the input factors using regression analysis. The optimal solution has been obtained using the desirability approach. The confirmation experiments have been performed on the optimal solution to verify with the experiment results. Results of the confirmation test shows that the developed mathematical are appropriate for the use in CI engine. • Use of Hydrogen (H 2) as alternate fuel in CI engine. • Experimental investigation of CI engine's performance parameters using Diesel and Hydrogen fuels. • Optimization of CI engine's performance parameters using Response Surface Method. • Performance parameters of H 2 fuelled CI Engine increased at higher compression ratio under varying load condition. [ABSTRACT FROM AUTHOR]

The paper proposes a methodology for designing intelligent systems of autonomous distributed hybrid power complexes (ADHPC) ensuring a minimum level of energy consumption from the national external grid as well as diesel power plants used to deliver the power to regional households, and industrial consumers. It will be realized because of the effective use of generated energy from renewable energy sources in such ADHPC systems by considering their both normal and emergency operating modes. In doing so, ADHPC will not only help offload the existing power grid during peak demand, but also allow for significant process efficiencies in energy production from renewable energy sources (RES), including "green" hydrogen: for instance, the excess energy is accumulated during the period of its excess and is provided back to power consumers in the period of shortage, the electricity losses are reduced since effective management is applied for power flows circulating in the ADHPC systems. The methodology includes the following stages (subtasks): development of the structure of a distributed hybrid system for generating and transporting electricity from sources to consumers; development of a system for diagnostics of failures of generating units and wire breaks in sections of local power transportation networks and management based on the diagnostics results of power flows circulating in the ADHPC systems for both normal and emergency modes. Therefore, a balance of power capacities and minimization of their losses are ensured. [ABSTRACT FROM AUTHOR]

• We employed MRA to specify the authentic empirical effect based on 328 estimation results from 33 primary studies. • Financial development leads to higher renewable energy consumption / use / capacity / production according to the MRA. • There is no publication bias in the existing literature. • The authentic empirical effect may change depending on financial development or renewable energy indicators used, time period covered, the unit analyzed, and the estimation technique employed. • There is an omitted variable bias in the existing literature. The current paper tries to determine and quantify the authentic empirical effect of financial development on renewable energy beyond publication selection bias, if any, based on 328 estimation results from 33 primary studies that were published or presented over the period of 2009-2022. Bivariate and multivariate FAT-PET analyses were used as tools of meta-regression analysis. A positive significant authentic empirical effect of financial development on renewable energy is found as a first contribution. Hence the results support Hypothesis 1; by offering more reliable, efficient, and less costly funds to investors; whether private or public, financial development boosts renewable energy. An absence of publication bias is resulted regarding the overall findings of the primary studies or design characteristics (moderating variables) as a second contribution. Based on the results for moderating variables, the authentic empirical effect may change in direction and magnitude due to the financial development or renewable energy indicators used, the time period covered, the unit analyzed, and/or the estimation technique employed as a third contribution. Omitted variable bias is found in the existing literature analyzing this subject. [ABSTRACT FROM AUTHOR]

As the solar energy utilization technology for renewable clean energy, actual parabolic trough receivers are subject to tracking errors and absorber tube installation errors, and the bellows and Kovar ring under these errors have a significant impact on the receiver's safety. Based on the MCRT-FVM-FEM principles in this paper, a receiver's optical-thermal-stress mathematical model is modeled and the thermal-stress performance and safety of the receiver's key components under two errors are evaluated. The correlation between the bellows and Kovar ring's performance and the two errors is analyzed. The results demonstrate that the lower tracking errors and larger installation errors markedly increment the absorber's deformation and have a negative impact on the receiver safety. Bellows and Kovar ring's asymmetrical temperature distribution causes variable swell and uneven stress under tracking and installation errors. Temperature gradient variation of bellows is more sensitive under errors than Kovar rings. Kovar ring's compressive stress rises substantially as the Y-directional installation error varied from −15 mm to 15 mm compared to other errors. With tracking errors exceeding 8 mrad, bellows' tensile stress and Kovar ring's compressive stress diminish under installation error. Thus, larger tracking errors significantly reduce the threat to the receiver when installation errors exist. [ABSTRACT FROM AUTHOR]

With the high penetration of renewable energy, its intermittency and volatility also bring challenges to traditional power system such as maintaining reliable operation of system and improving the utilization of renewable energy. Under the background of Energy Internet (EI), energy router (ER) emerges as the times require. Aiming to improve the ability of support of energy storage units to DC buses and suppressing power shocks both inside and outside the ER, in this paper, an ER based on multi-hybrid energy storage system (MHESS) is proposed. As the principle of maximizing the utilization of renewable energy, a corresponding energy coordinated management strategy is proposed. Charging/discharging timespan optimization model is established to ensure MHESS as available as possible. The reference power of MHESS is allocated based on the proposed optimization model. Simulation analysis of different working conditions in 4 operation scenarios are carried out and the results show that the power oscillation on different buses of ER can be dampened within 0.1s and the bus voltages fluctuate within 2% while operation scenarios are switched, which verifies the feasibility and effectiveness of the proposed energy coordinated management strategy. [ABSTRACT FROM AUTHOR]

Renewable energy is regarded as an effective method to alleviate environmental pollution and accelerate the green transition in China. This paper systematically investigates the impact of financial inclusion on renewable energy demand by using S-GMM model based on provincial data in the green finance era. This paper also analyzes the asymmetry, heterogeneity, and mediating mechanism in the nexus between financial inclusion and renewable energy demand, and highlights the following findings: (1) Improved financial inclusion can promote renewable energy development in China and present the characteristics of green finance; (2) the impact of financial inclusion on renewable energy demand is asymmetric and heterogeneous; specifically, this impact is much higher in northern China and the regions with higher renewable energy development; and (3) wind and photovoltaic power generation are effective mediators between financial inclusion and renewable energy industry, while the mediation effects of hydropower and nuclear power are not significant. New evidence in this study is presented for the achievement of green transition in China, as well as practical policy implications for improving financial inclusion and increasing renewable energy consumption. For instance, fiscal and tax incentives and green investment subsidies in the renewable energy sector need to be further improved. • This study explores the impact of financial inclusion (FI) on renewable energy demand (RED) in China. • Asymmetry, heterogeneity, and the mediating mechanism are further discussed. • Increased FI can promote RED , which presents the characteristics of green finance. • The impact of FI on RED is asymmetric and heterogeneous. • Wind and photovoltaic power are effective mediators between FI and RED. [ABSTRACT FROM AUTHOR]

Despite their economic success, the BRICS countries have yet to achieve environmental sustainability. On the other hand, these countries will not be able to maintain their economic expansion if they do not protect the natural environment. In this regard, this paper intends to assess the effects of financial integration (globalization) on ecological footprint. The paper also considers other ecological footprint drivers, including economic expansion, urbanization, renewable energy and technological innovation. The research utilizes a dataset spanning from 1990 to 2018. The study employed the method of moments quantile regression (MMQR) approach, which is robust to cross-sectional dependence and slope homogeneity issues. The outcomes from the MMQR disclose that the effect of financial globalization on ecological footprint is positive across all quantiles (0.1–0.90), thus validating the pollution haven hypothesis (PHH) in the BRICS nations. Furthermore, both renewable energy and technological innovation curb ecological footprint across all quantiles (0.1–0.90). Moreover, technological innovation is proven to impact the environment positively across all quantiles (0.1–0.90) via the path of urbanization. As a result, technological innovation is projected to help the BRICS nations achieve sustainable urbanization. The DOLS, FMOLS, FE-OLS outcomes also validate the outcomes of MMQR. Based on these results, policies were proposed. • MMQR applied to integrate asymmetric effects. • Renewable energy consumption and technological innovation derive ecological sustainability. • Financial integration-led Pollution-haven-hypothesis is confirmed. • Economic growth and urbanization lead to higher ecological footprints. • Technology innovation neutralizes the negative impact of urbanization on ecological sustainability. [ABSTRACT FROM AUTHOR]

This paper evaluates the impact of climate policy uncertainty on renewable and non-renewable energy consumption in the United States over the quarterly data from 2000Q1 to 2021Q3. Economic growth and crude oil prices are added to the energy consumption functions as control variables. The paper considers several approaches to model both renewable and non-renewable energy demand. It is found that crude oil prices promote non-renewable energy demand and climate policy uncertainty reduces it. Surprisingly, the impact of economic growth on non-renewable energy consumption is positive but insignificant. It is also observed that economic growth promotes renewable energy demand, and crude oil prices reduce it. Furthermore, climate policy uncertainty positively affects renewable energy demand in the long run. Some policy implications are provided for reducing non-renewable energy consumption and promoting renewable energy use in the United States through climate policy implementation. • We examine the impact of the Climate Policy Uncertainty (CPU) on renewable and non-renewable energy consumption. • We use the quarterly data from 2000Q1 to 2021Q3 in the United States. • The CPU reduces non-renewable energy demand. • The CPU positively affects renewable energy demand in the long run. • Promoting renewable energy use through climate policy implementation is discussed. [ABSTRACT FROM AUTHOR]

As stated in Sustainable Development Goals number 6 and 13, clean water and sanitation and energy-related carbon emissions as climate action issues have emerged as serious issues within the United Nations. Around 150 countries rely on seawater desalination plants as their water resource. Reverse osmosis membrane technology is the most widely used seawater desalination technology for water supply. Taking water resources, developing renewable energy, and recycling resources have become the United Nations' core sustainable development goal. Therefore, this paper aims to provide an overview of renewable energy in reverse osmosis, especially newly developed renewable energy such as wave power. This paper includes technical issues, environment, and economic impact. In addition, compared with other energy sources, photovoltaic and hydropower energy utilization leads to a lower carbon footprint. Both energy produce a carbon footprint of around 0.08 kg CO 2 eq/m3. Control systems and energy storage management are the challenges in developing integrated renewable energy with reverse osmosis. Suitable pretreatment and the effect of direct use of renewable energy on the reverse osmosis process, especially on membrane and pump lifetime, should also be considered in future studies. [Display omitted] • Fluctuations and intermittence in wind and PV would affect on the process performance. • Energy storage management helps to keep the system stable • Water storage can assist in having enough water and store extra • PV and hydropower energy produce carbon footprint around 0.08 kg CO 2 eq/m3. [ABSTRACT FROM AUTHOR]

The paper addresses challenges arising from the unpredictable and probabilistic nature of wind speed and solar irradiance, leading to variable power production in renewable sources. Power imbalance issues in grids result from the difficulty in accurately estimating these variables. The study introduces an improved data-driven uncertainty set, utilizing a neural network trained with extensive historical data from a multi-microgrid system. This set efficiently identifies strong coupling and extracts characteristic scenarios, ensuring high reliability with a minimal number of scenes. The proposed probabilistic model, implemented in the coordination of pumped storage, wind, and solar power plants, incorporates energy limits and storage characteristics. A four-mode IEEE model for storage units allows quick response to system needs. Simulating storage unit states every hour, considering system load, output power, and energy limitations, optimizes power dispatch based on battery capacity. Additionally, the paper addresses the uncertainty in electric power demand in microgrids, proposing an improved data-driven uncertainty set obtained from a neural network. By eliminating unrealistic worst-case scenarios, the approach accurately captures system characteristics, maintaining high reliability while significantly reducing convergence time. The proposed uncertainty set is applied in a novel two-stage robust optimization dispatch model, transforming the optimization problem into a mixed-integer linear programming problem, and solving it using a column and constraint generation algorithm. Numerical case studies verify the feasibility and superiority of the proposed approach in terms of economy and convergence performance compared to existing robust optimization methods. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

Challenges and future perspectives of desalination integration are presented. [Display omitted] • Different optimized models for desalination technologies integration are summarized. • The control strategies of RES-desalination for reducing environmental are discussed. • Impact of desalination process innovation on energy saving and emission reduction. In the present framework, desalination, as an energy-intensive industry, has garnered increased attention due to the imperative need for reducing energy consumption. In this paper, various challenges in the integration and optimal design of desalination processes have been presented. The energy consumption, energy supply method, water production method and improvement measures of various desalination are studied in detail, of which energy consumption is a major aspect. This article summarizes the integration modes of different desalination technologies. Low integration density, inadequate energy utilization and unsystematic theory guidance have been the focus of research. Operational strategies and optimal design methods for the integration of renewable energy and desalination technologies are studied in detail. The integration of renewable energy emerges as a pivotal trend, contributing significantly to the reduction of carbon footprints and costs. Additionally, the significance of recently developed desalination processes, such as pre-treatment process, equipment enhancements and advanced materials have been discussed. Furthermore, various unresolved issues in de integration desalination technologies system have been investigated in the paper along with the possible solutions to address the reported open issues. By exploring the integration of desalination technologies, the paper aims to provide valuable insights for enhancing the efficiency of commercial desalination plants. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [ABSTRACT FROM AUTHOR]

• The thermal, rheological, and optical properties of ferrofluids and how they change with magnetic fields were discussed. • The utilization of ferrofluids in solar energy systems was detailed in a state-of-the-art analysis. • The recommendations aimed to optimize the use of ferrofluids and magnetic fields in energy systems to enhance performance. Solar energy technologies play a crucial role in the transition to sustainable energy sources; however, there is an ongoing challenge in optimizing their efficiency and performance. This review paper thoroughly exposes the potential for enhancing solar systems by incorporating ferrofluids and utilizing magnetic fields. It provides a comprehensive examination of the rheological, thermal, and optical properties of ferrofluids, as well as their behavior when exposed to magnetic fields. The paper emphasizes the ability of ferrofluids to improve heat transfer efficiency, adapt to changing conditions, and enable precise control in the conversion of solar energy. Furthermore, the review addresses the obstacles and limitations associated with integrating ferrofluids into solar technologies, proposing potential solutions and outlining future research directions. [ABSTRACT FROM AUTHOR]

The increase of Renewable Energy (RE) production to fight the climate crisis is posing new technological and financial challenges, due to the availability and variability of RE Sources (RES). These challenges can be addressed by selecting the most suitable mix of RES to optimise power production, to assure grid resilience and to promote local energy use. To facilitate the selection of such combination, this paper presents an original methodology that allows to compare mixing scenarios with different RES, also in presence of batteries and backup system. It simultaneously optimises the energy surplus with respect to the eventual external electrical load and the missing energy with respect to the same electrical load. This method, which can cope with isolated or plugged-to-grid systems, is here applied to a novel case study, an oil&gas platform under decommissioning, located in the Adriatic Sea (Italy). The RE production from wind, wave and solar panels is supposed to support other activities for the platform reuse, such as aquaculture, monitoring and mineral deposition. In this case, solar energy is providing the greatest contribution to the optimal mix in terms of production, while wave energy assures the most relevant contribution in terms of continuity. [ABSTRACT FROM AUTHOR]

With the rising usage of fossil fuels, there is an urgent need to develop new technologies specifically based on renewable energy sources to power the vehicles running on fuel. A fuel cell is an electrochemical cell that is used to convert the chemical energy of a fuel directly to electric power. Fuels cells possess advantages such as smaller size, high efficiency, silent operation, etc. However, there can be significant variations in the size and power output of the fuel cells depending upon the application. The focus of this paper is to estimate the performance of an integrated system comprising of Polymer Exchange Membrane Fuel cell (PEMFC) and vapour adsorption refrigeration system to produce electric output and cooling effect simultaneously. The adsorption system in this study is based on activated carbon and methanol combination. The effect of operating parameters such as the operating temperature, current density and evaporator temperature on the energy and exergy efficiency of the system is presented. The study shows a remarkable improvement in the performance of the integrated system compared to PEMFC alone. The results show that the system energy and exergy efficiency decrease as the current density value increases. Maximum system energy and exergy efficiency of 63.01% and 29.88% are achieved. In addition, a maximum energy efficiency of 65.39% was reported at an evaporator temperature of 5 °C and a current density of 0.8 A/cm2. • Thermal integration of PEMFC with vapour adsorption refrigeration cycle is studied. • Energy and exergy efficiency of PEMFC with and without VADRC is analyzed. • The influence of key operating parameters on system performance is investigated. • A maximum system efficiency of 66.83% is achieved after incorporating VADRC. [ABSTRACT FROM AUTHOR]

In this paper, we explore the co-movements between renewable and non-renewable energy sources and CO 2 emissions and GDP per capita in Saudi Arabia, respectively. Using the spectral Granger causality approach, our results suggested that non-renewable energy sources lead to carbon emission expansion in the frequency domain. Taken together, a significant causal relationship from fossil to economic growth is perceived over the long-term horizon while renewable energy source drives economic growth over different frequencies and considerably contributes to carbon emissions reduction. The wavelet plots revealed strong discrepancies in all variables in the time-frequency space. While non-renewable energy sources indorsed the economic growth across short-and medium-term scales and contribute to a polluted environment, renewable energy consumption has a substantial effect on carbon emission drop and on economic growth in the short-term. The multiple wavelet outcomes show that renewable energy may not only stimulate the economic growth but also promote sustainable and cleaner environment. The combined effects of non-renewable energy sources rise the carbon emissions. Thus, Saudi's government is counselled to promote the green energy investments and accelerate the transition to renewable energy production as its use as a substitute of fossil fuels carries advantages and opportunities alternating from environment to social-economic. [Display omitted] [ABSTRACT FROM AUTHOR]

Global warming is one of the most important environmental problems in the world. One might state that the most potential considerable cause of global warming is the increase in greenhouse gas emissions in the atmosphere. The commonly suggested method used to struggle with this potential problem is to consume renewable energy sources instead of fossil fuels. In today's World, where the rate of urbanization is very high, the research on the effect of the energy demand of the residential sector on global warming has become a crucial research topic in the energy and climatic literature. Among different solar sectors, the residential sector is a major energy consumer. Considering the residential, commercial, and industrial solar sectors, the residential solar sector has become a major component of total solar energy. It accounts for approximately 43% of total solar. On the other hand, to the best of my knowledge, there exists no empirical study in the literature considering the influence of residential solar consumption on environmental quality. Thus, determining the effect of the most used energy source, residential solar, energy consumption on the environmental quality has arisen the key research problem of this paper. This research analyzes the effects of residential solar energy usage on CO 2 emissions for the period 1989:1–2020:1 in the USA. It has been observed throughout Morlet wavelet analyses that the use of residential solar energy has a strong effect on mitigating CO 2 emissions in the 1–2 year frequency. Eventually, this paper provides relevant potential energy policies that can enhance the efficiency of residential solar energy consumption. Partial wavelet coherence (RSolar-CO 2 || Coal, Hydro, IP), 1989:1–2020:1. [Display omitted] • Considers the impact of residential solar consumption (RSolar) on CO 2 emissions. • Follows the data for the USA for the monthly period 1989:1–2020:1. • Launches wavelet models in which RSolar, CO 2 , Coal, Hydro, and IP are employed. • Reaches the negative impact of RSolar on CO 2 in the USA for the period 1989:1–2020:1 at 1-2 year-cycle period. • Through potential energy policies, residential solar energy consumption efficiency should be increased. [ABSTRACT FROM AUTHOR]

The dispatch-down of excess wind energy is a growing concern, especially for countries integrating high levels of variable renewable energy. Demand flexibility presents an opportunity to move consumers loads to periods of excess wind energy, which could provide numerous values to the system. While previous research has focused on managing wind energy curtailment (a system-wide issue), much wind energy is rejected due to constraint (a local issue) and hence can only be resolved by local load-on-demand. This paper provides a framework to assess the value of demand flexibility for managing wind energy constraint and curtailment. A methodology to determine the optimal number of subscribers to yield sufficient reduction in excess wind energy while ensuring reasonable cost savings for the subscribers is developed. Analysis shows that this optimal number of subscribers could provide a 67% reduction in constraint and a 74% reduction in curtailment. Consumers can save up to £220 per year, depending on their priority in the dispatch process. A 10-MW wind farm could earn £19,400 annually from avoided curtailments. System operators could save up to 78% on constraint payments. The paper also assesses the network impact of flexible loads and provides a methodology for calculating the heat-pump hosting capacity of the grid. • A framework for utilizing wasted wind energy for heating homes is investigated. • Currently wasted wind energy could save fuel poor households up to £220 per year. • A 10 MW wind farm could earn about £20,000 annually from avoided curtailment. • System Operators could save up to 78% on constraint payments. • Mathematical model to determine heat pump hosting capacity of a grid is developed. [ABSTRACT FROM AUTHOR]

Given the role that renewable energy consumption plays in transitioning to a low-carbon economy, it is critical for policymakers to understand its determinants. Although uncertainty has increased significantly since the early 2000s, little is known about its effect. To fill this gap, the paper provides novel evidence of the effect of policy-induced uncertainty on renewable energy consumption after controlling for income, institutions and innovation in G7 countries over the period 1997–2019. Using the nonlinear autoregressive distributed lag model, the paper reveals its asymmetric effects in the long run, implying that both a negative and a positive shock in lagged uncertainty reduce renewable energy consumption. The effect of uncertainty proved to be significant in the same direction, but not asymmetric in the short run. However, the effect of all other variables remained insignificant in the short run, which is not the case in the long run. Indeed, the results confirm that income and investment in research and development drive renewables, while it is hindered by more economic freedom in the long run. Therefore, consistent, clear and well-communicated energy and economic policies are called for, along with technological advances, as they can help minimize policy uncertainty and promote renewable energy use. [ABSTRACT FROM AUTHOR]

The continuous increase in global energy consumption as a result of rapid population growth, combined with the detrimental impact of fossil fuels on the atmosphere, has made it critical to extract renewable energy through various technologies and turn it into electricity. A hybrid photovoltaic-thermal collector can be an innovative alternative to harness renewable energy. The utilization of hybrid photovoltaic-thermal solar collectors is increasing day by day due to its advantages. This type of collector can generate both heat and electricity at the same time and convert absorbed solar radiation more efficiently than a solar thermal collector or a typical photovoltaic module. In order to improve the performance of the hybrid photovoltaic-thermal (PV/T) solar collector, nanofluid can be an effective solution. It has been found that serpentine, rectangular, microchannel, sheet and tube, etc., are some categories of geometries utilized in the PV/T system. Both experimental and computational studies were conducted related to nanofluids application in PV/T collectors in recent years. Most of the studies were done utilizing some common nanofluids, e.g., Al 2 O 3 , CuO, ZnO, and SiO 2. It has been noticed that utilizing nanofluids significantly enhances overall performance, thermal and electrical efficiency, heat transfer characteristics, and exergy. This paper comprehensively reviewed various aspects of using nanofluids, including energy efficiency, exergy efficiency, overall efficiency, heat transfer coefficient, daily yield, power generation, entropy production, exergy loss, and temperature drop in hybrid PV/T collectors in a systematic way. Besides, the paper incorporated all recent findings and included experimental, numerical, and combined studies in the review. • MWCNT nanoparticle provides more efficiency compared to oxide-based nanoparticles. • Ag–H 2 O can enhance thermal output up to 13% than the water-cooled system. • SWCNT nanoparticles improve daily yield and have a relatively cheap production cost. • Energetic and exegetic performance can be increased by utilizing nanoparticles. • Using nanoparticles notably enhance power generation rate, and heat transfer ability. [ABSTRACT FROM AUTHOR]

The transition to renewable energy is key for sustainable development. Therefore, one of the sustainable development goals (SDG) of United Nations (UN) is to shift towards clean energy. However, in many resource-rich countries several factors can stand as barriers towards the transition process. In this regard, this paper examines the influence of higher oil price, CO 2 emissions, and income on renewable energy consumption in Iran from 1980 to 2019, employing General to Specific (Gets) modeling approach. Estimation results indicated that oil price and CO 2 emissions both have statistically significant and negative impact on renewable energy consumption. The negative influence of higher oil prices on renewable energy consumption may be interpreted as sign of satisfaction coming from higher oil prices, which postpones the transition from traditional energy sources to renewable for Iran. Furthermore, we concluded that income does not have a statistically significant influence on renewable energy use. The paper discusses alternative policies to promote renewable energy consumption. • The effect of higher oil price on renewable energy consumption was studied. • A novel version of General to Specific (Gets) modeling approach was employed. • We found significant, negative impact of oil price on renewable energy use in Iran. • The paper discusses alternative policies for Iran to promote renewable energy use. [ABSTRACT FROM AUTHOR]

Hydrogen can be produced from onsite renewable energy, energy from the power grid, or a combination of both. While the cost of grid energy is driven by the energy prices, onsite renewable investments are driven by the levelized cost of renewable energy. Energy prices can widely vary in time and in different locations, potentially having a large impact on the annualized cost of hydrogen (ACOH). Renewable sources can also vary significantly for different locations and seasons. In this paper, we develop a semi-empirical model to find key ACOH locational drivers and trends. The model finds the optimal capacity of the onsite solar and wind generators and the electrolyzer, together with the optimal use of grid energy. We found that an optimal balance between onsite renewable investments and grid energy use is strongly driven by the type of energy price (fixed or variable) and location. • Sizing onsite renewables and electrolyzers for different grid energy prices. • Onsite renewables versus grid energy, largely driven by energy prices and location. • Combined solar-wind capacity factor is key driver of the optimal energy use. • Significant hydrogen production from low-cost grid renewable energy. • Transmission congestion plays a key role in increasing the use of grid renewable energy. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of green finance and renewable energy on energy efficiency in E−7 economies. We analyzed the nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency. We collected data from 1985 to 2017 and applied the NARDL and 2SLS methods. The results reveal that the differences in green finance development in the E−7 region are as follows: China (0.61), Brazil (0.55), India (0.53), Indonesia (0.49), Mexico (0.37), and Russia (0.39). In 2019, the Gini coefficient was the largest in Russia (0.57), followed by Turkey. Based on empirical findings, the largest barrier to green energy efficiency is insufficient private and governmental investment in the energy sector to improve access to power, to increase energy security and promote economic growth in an environmentally sustainable manner. The findings point to a promising but vulnerable future for renewable energy and energy efficiency deployment in E−7 countries. This paper emphasizes that green financing and renewable energy policy limitations must be addressed to realize the funding potential of energy efficiency in E−7 countries. • We have analyzed the barrieres for renewable energy and energy efficiency. • Non-linear and asymmetric effects is observed on energy efficiency. • We have applied NARDL model to examine the relationship among variables. [ABSTRACT FROM AUTHOR]

Economic, technological, and environmental causes are moving energy toward smart distribution networks. The change from fossil fuels to renewable energy sources is extremely environmentally friendly in both the building and transport sectors. Microgrids could be efficiently used in remote areas utilizing renewable energy resources for supplying different energy demands namely power, heat and cold. This paper presents a mixed-integer linear programming (MILP) model for optimizing planning and sizing decisions in microgrids connected to main grid. Planning decisions the amount of generation of each distributed generation (DG) technology and the amount of power transmission to other nodes. Also, sizing of different DGs including photovoltaic and combined heat and power facilities are performed by the proposed model. According to the results, the model is able to optimize sizing and planning decisions in grid-connected microgrids. [ABSTRACT FROM AUTHOR]

This paper presents and compares three approaches to deal with the uncertain nature of energy supply and demand in the problem of optimal sizing of a stand-alone, reliability-constrained hybrid renewable energy system. The system is composed of wind turbines, photovoltaic solar panels, a battery bank, and a diesel generator. The proposed approaches are: (a) adaptive robust optimization with unmet demand as the (un)-reliability metric, (b) scenario-based robust satisficing, and (c) stochastic-free robust satisficing. A column-and-constraint generation algorithm is developed to solve the adaptive robust optimization problem. Furthermore, the theoretical connection between the proposed approaches is drawn, and their numerical performances are compared, in terms of optimal solution cost and reliability, through computational experimentation on a realistic case study. Numerical results show that both the computational times and the out-of-sample performances of the optimal solutions obtained from the two proposed robust satisficing approaches outperform that of the adaptive robust optimization approach, providing a strong justification for their application • Robust optimal design of a stand-alone hybrid renewable energy system. • Adaptive robust optimization versus robust satisficing optimization. • Optimization under the uncertainty of demand and supply. [ABSTRACT FROM AUTHOR]

Hydropower renewable energy is known to be pro-environment: flexible and affordable. Above all, it is compatible with other energy frames and also with the policies that otherwise prove to be inimical towards its future. Where environmental stability is concerned it needs an assiduous study coupled with research by the policymakers to get around knowing the different perspectives of hydropower renewable energy. The study has taken nine different and diverse perspectives of hydropower renewable energy into account to stop the process of environmental degradation. EKC framework has been put to use in a case study of South and East Asia economies. Time period has been selected from 1975 to 2020 to measure the long-term impact. GMM model has been used for the panel estimation besides getting future dynamics. The results which have come about confirmed EKC in the selected countries. Non-renewable energy (coal and gas) had an adverse impact on environmental stability. However, switching towards hydropower renewable energy can mitigate these environmental losses. Empirical findings have proved that more use of clean energy production can bring about a considerable amount of environmental stability. Insofar as East Asia economies are considered they have reached the second stage of EKC with a turning point of $13844 (per capita income). This paper, therefore, suggests that the future depends upon renewable hydropower energies in South and East Asia economies. That being said, there appears to be a dire need to undertake the role of various socioeconomic and geographic factors that influence hydropower renewable energies to check the long-term effect. [Display omitted] [ABSTRACT FROM AUTHOR]

• Accurately modeling the blockchain system based on the miners' energy consumption during the data transactions process. • Offering a two-stage structure of energy consumption management of miners through an IPS-based placement algorithm. • Developing a distributed energy architecture among blockchain miners and the electrical grid and renewable energy resources located on the grid inspired by the PDMM concept. Addressing the blockchain technology (BCT) challenges, such as the high energy consumption is unavoidable in smart power systems to take maximum advantage. As an antithetical point, there is a structural duality between using BCT in the electrical grid due to its advantages and energy consumption. To this end, this research work is an inclination toward controlling the miner's energy consumption based on a realistic and efficacious two-stage energy mechanism toward the distributed energy concept and optimal placement of data mining devices. In this circumstance, such a new structure allows miners to mainly sustain their hash rates as a prominent index for security achievement and optimally decrease their cost. This paper suggests a novel distributed model for miners coincided with the smart electrical grid getting inspired by the Prima-Dual Method of Multipliers (PDMM) based distributed approach to settle down the needed power bartering between miners and energy supply resources. In addition, for a similar purpose, it seems to reach the ideal resolution needs to perform the modified reaffirmation of miners (the mining pool) within the secured grid. To execute this task, this research recommends the Intelligent Priority Selection (IPS) techniques as well. When all is said and done, the result of this approach can aid researchers with performing in the field of improving social advantages by the usage of the suggested method. [ABSTRACT FROM AUTHOR]